Data from: No support for solar radiation as a major evolutionary driver of malar stripes in falcons
Data files
Nov 30, 2024 version files 1.83 MB
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README.md
10.62 KB
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Vrettos_Reynolds_Amar_2024_Data.csv
1.82 MB
Dec 18, 2024 version files 1.83 MB
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README.md
10.67 KB
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Vrettos_Reynolds_Amar_2024_Data.csv
1.82 MB
Abstract
The malar stripes of falcons (Falco spp.) are often hypothesised to function by reducing the amount of solar glare reflected into the falcon’s eyes while hunting, thereby aiding foraging efficiency in bright conditions. This “solar glare hypothesis” is supported by intraspecific trends in Peregrine Falcons (Falco peregrinus), in which populations inhabiting regions of higher average annual solar radiation exhibit larger and darker malar stripes on average. Here, we extend the methodological approach previously used in Peregrine Falcons to examine both intra- and interspecific relationships between solar radiation and malar stripe morphology across all extant falcon species, thereby providing a more robust test of the hypothesis that falcon malar stripes evolved as an adaptation against negative visual effects of solar glare. We obtained web-sourced photographs of all extant falcon species, taken across each species’ geographic range, and related mean breeding season solar radiation at each photograph location to the size and darkness of the birds’ malar stripes, simultaneously testing for intraspecific and interspecific relationships between malar stripe characteristics and solar radiation, and including phylogeny and relevant ecological traits as covariates. We found no consistent interspecific relationship between solar radiation and malar stripe characteristics Likewise, in 38 out of 39 species, malar stripe characteristics were not positively intraspecifically related to solar radiation, with only Peregrine Falcons showing trends towards larger and darker malar stripes in brighter regions. Falcon malar stripes are thus unlikely to represent an adaptation against visual effects of solar glare, and their adaptive significance is more likely to be explained by crypsis or social signalling, if indeed they do represent an adaptive trait. Malar stripes may have become co-opted for solar glare reduction in Peregrine Falcons due to the species’ specialisation for high-speed aerial hunting, although the intraspecific patterns observed may alternately be explained by phylogeography.
README: No support for solar radiation as a major evolutionary driver of malar stripes in falcons
https://doi.org/10.5061/dryad.gxd2547wq
Description of the data and file structure
The data file contains photograph metadata for user-submitted photographs of 39 falcon species (including the name of the photographer, date and location at which the photograph was taken, GPS coordinates, photographer comments, and species, sex, and subspecies identification) from the Macaulay Library (https://www.macaulaylibrary.org/), GBIF (https://www.gbif.org/), Flickr (https://www.flickr.com), Oiseaux (https://www.oiseaux.net), BirdGuides (https://www.birdguides.com), the African Bird Club Image Database (https://africanbirdclub.org/afbid), and the Oriental Bird Club Image Database (now hosted at https://www.macaulaylibrary.org/oriental-bird-images/), as well as from private photographers. For each species and photograph location, the data file also contains mean monthly solar radiation (W/m^) measurements at each photograph's GPS location, extracted from the TerraClimate dataset (http://www.climatologylab.org/terraclimate.html) using Google Earth Engine, and averaged over the six-month period representing the species' or population's breeding season (March-August for boreal summer breeders and September-February for austral summer breeders), representing the 30-year (1991-2020) average breeding season solar radiation for the species or population at the photograph GPS location. Species trait information in the form of body mass (g) and hand-wing index estimates derived from AVONET (https://opentraits.org/datasets/avonet.html) for all 39 falcon species is also included in the data file, along with numerical scores representing prey preference and habitat openness assigned by the study authors, based on information in the available literature. For each individual bird in each photograph, the data file also contains scores of malar stripe length, width, and darkness, based on subjective visual scores assigned by a single observer on a scale of 0-10, along with scores of the bird's head orientation and degree of plumage distortion. Data for this study were collected and analysed between 2020 and 2022.
The R script for this study contains code for calculating correlations between malar stripe and species trait variables, constructing "spatiophylogenetic" models, measuring relationships between malar stripe variables, species trait variables,and solar radiation data, and constructing all figures used in the publication. Steps for running the script and explanation of outputs are provided in the descriptive text within the R code file, and in the associated publication.
Files and variables
File: Vrettos_Reynolds_Amar_2024_Data.csv
Description:
Variables
- Image_ID: Identification number for the photograph in the relevant online database (text)
- Individual: ID term denoting the individual bird in the photograph, to enable separate measurements for different individuals in photographs containing multiple birds (categorical, values a-d)
- Species: Name of the "species" to which the individual is coded as belonging in the analysis, represented by the species scientific name and (for species with sexually dichromatic facial plumage) an "M" or "F" marker denoting sex (categorical)
- Scientific_Name: Scientific name of the species (categorical)
- Common_Name: Common name of the species (categorical)
- Tree_Name: Specific name of the species as it appears in the phylogeny derived from Fuchs et al. (2015)
- Subspecies: Subspecies of the bird in the photograph, as estimated by the photographer (categorical); birds of unknown subspecies or from monotypic species are represented by missing values (N = 10341)
- Sex: Sex of the individual bird in the photograph, as estimated by the photographer and/or the observer (categorical, values "M", "F" or "U"); birds of unknown sex are coded as "U" for "unknown" (N = 7560)
- Length: Malar stripe length score assigned by the observer (numeric, values 0-10)
- Width: Malar stripe width score assigned by the observer (numeric, values 0-10)
- Darkness: Malar stripe darkness score assigned by the observer (numeric, values 0-10)
- Head_Angle_1: Approximate orientation of the bird's head in terms of pitch rotation, or rotation around the horizontal axis, estimated by the observer (numeric, values "180", "90", or "45")
- Head_Angle_2: Approximate orientation of the bird's head in terms of yaw rotation, or rotation around the vertical axis, estimated by the observer (numeric, values "135", "90", "45", "0", "-45", or "-90")
- Head_Angle_3: Approximate orientation of the bird's head in terms of roll rotation, or rotation around the anterior-posterior axis, estimated by the observer (numeric, values "45", "0", or "-45")
- Plumage_Distortion_1: Degree of plumage distortion as a result of vertical feather compression due to the bird sitting slumped or hunched over, scored according to a visual scale by the observer (numeric, values 1-4)
- Plumage_Distortion_2: Degree of plumage distortion as a result of ptiloerection, scored according to a visual scale by the observer (numeric, values 1-3)
- Uniform_Plumage: Binary variable denoting whether the species or morph of the bird in the photograph was denoted as having uniformly-coloured facial plumage (binary, values "0" or "1")
- Coords Added: Whether GPS coordinates were available for the photograph, or whether GPS coordinates for the written photograph location were added by the study authors (TRUE/FALSE, where TRUE = GPS coordinates added by the study authors)
- Country: Name of the country in which the photograph was taken (categorical)
- Year: Year in which the photograph was taken (numeric). Photographs taken on unknown dates are represented by missing values (N = 473)
- Month: Number of the month in which the photograph was taken (numeric). Photographs taken on unknown dates or for which only the year is known are represented by missing values (N = 478)
- Day: Day of the month on which the photograph was taken (numeric). Photographs taken on unknown dates or for which only the year/month are known are represented by missing values (N = 516)
- Notes: Observation notes supplied by the observer, in cases of birds misidentified or mis-sexed by the photographer (text)
- File_Name: Name of the cropped .tif image file derived from the photograph used for visual scoring (text)
- SRad_mean: Mean monthly solar radiation (W/m^2) for the GPS location of the photograph, averaged over the six months (Mar-Aug or Sep-Feb) representing the relevant species' and population's breeding season (numeric)
- Body_Mass: Mean body mass (g) value for the species as recorded in AVONET (numeric)
- HWI: Hand-wing index for the species as recorded in AVONET (numeric)
- Prey_Preference: Score assigned by the study authors based on the proportion of bird prey in the species' diet, with higher values representing a higher degree of specialisation on bird prey (numeric, values 1-4)
- Habitat_Openness: Score assigned by the study authors based on the degree of habitat openness or dependence on forest habitats for the species, with higher values representing more open (less forested) habitats (numeric, values 1-5)
Some photograph metadata (download URLs, photographer names, license information, and embedded GPS coordinates) have been removed from the data file at the request of Dryad to ensure compliance with the CC0 license waiver. Since the GPS coordinates of the photographs is required to run the code, access to these and other photograph metadata are available upon request from the study authors.
Code/software
The code for this publication was built and tested in R version 4.2.0 and is available in the R script "Vrettos_Reynolds_Amar_Code.R" (available at https://zenodo.org/records/14096759). As many of the required packages for this code have been deprecated in later releases, it is recommended that this code be run in R versions 4.2.3 or earlier. Instructions for running the code are provided in the R code file.
The following R packages must be installed in order to run this code:
- AICcmodavg
- ape
- dplyr
ggplot2
ggregplot
ggridges
ggtree
INLA
INLAutils
inlabru
magrittr
maps
nlme
patchwork
PerformanceAnalytics
phyr
phytools
psych
raster
readr
remotes
scico
sf
sp
summarytools
tidyr
Installation information and Github links for the R packages ggregplot, ggtree, INLA, and INLAutils are provided in the R code.
This code makes use of the "spatiophylogenetic" modelling approach developed by Dinnage et al. (2020) (https://doi.org/10.1098/rspb.2019.2817). All data and code from this publication and a tutorial for constructing "spatiophylogenetic" Bayesian models using INLA are available at the following Dryad link: https://doi.org/10.5061/dryad.jh9w0vt73.
This code also makes use of a phylogeny of the Falconidae derived from Fuchs et al. (2015) (https://doi.org/10.1016/j.ympev.2014.08.010). The .phy file used in this study is available upon request and with permission of the original authors.
Access information
Data were derived from the following sources:
- Macaulay Library at the Cornell Lab of Ornithology (https://www.macaulaylibrary.org/)
- Global Biodiversity Information Facility (https://www.gbif.org/)
- Flickr (https://www.flickr.com/)
- Oiseaux (https://www.oiseaux.net/)
- BirdGuides (https://www.birdguides.com/)
- African Bird Club Image Database (https://www.africanbirdclub.org/afbid/)
- Oriental Bird Club Image Database (now hosted at https://www.macaulaylibrary.org/oriental-bird-images/)
- TerraClimate (https://www.climatologylab.org/terraclimate.html)
- AVONET (https://opentraits.org/datasets/avonet.html)
Methods
Photograph metadata for user-submitted photographs of 39 falcon species (including the name of the photographer, date and location at which the photograph was taken, GPS coordinates, photographer comments, and species, sex, and subspecies identification) were downloaded from the Macaulay Library (https://www.macaulaylibrary.org/) and GBIF (https://www.gbif.org/) online databases, using the websites' export tools, with additional photographs sourced from Flickr (https://www.flickr.com), Oiseaux (https://www.oiseaux.net), BirdGuides (https://www.birdguides.com), the African and Oriental Bird Club Image Databases (currently hosted at https://africanbirdclub.org/afbid and https://www.macaulaylibrary.org/oriental-bird-images/, respectively), and private photographers via email correspondence. All photographs were then downloaded using the list of image URLs and filtered to include only photographs of adult birds and those taken within the breeding or resident range for the species. For species in which resident and wintering populations overlap in geographic range, photographs taken within the area of overlap were also filtered to only include those taken within the migratory population's breeding season, using species range maps provided by BirdLife International (https://datazone.birdlife.org/). For each species, a random selection of up to 1000 photographs was then selected for analysis, with this selection process repeated until the maximum number of 1000 usable photographs for each species was reached, or until there were no more photographs available. Mean monthly solar radiation (W/m2) measurements at each photograph's GPS location were then extracted from the TerraClimate dataset (http://www.climatologylab.org/terraclimate.html) using Google Earth Engine, and averaged over the six-month period representing the species' or population's breeding season (March-August for boreal summer breeders and September-February for austral summer breeders), representing the 30-year (1991-2020) average breeding season solar radiation for the species or population at the photograph GPS location. For photographs which did not have user-submitted GPS coordinates available, the GPS coordinates for the written photograph location were sourced from Google Maps. Photograph metadata and solar radiation data were collected between March 2020 and May 2021.
For each individual bird in each photograph, a single observer then scored the characteristics of the malar stripe according to an eleven-point visual scale constructed for this purpose. Three aspects of the malar stripe were quantified: length, width, and darkness. The same observer also scored the angle and position of the bird's head in each photograph according to a visual scale (see ReadMe for details). Photographs were cropped to include only the bird's head, pooled into a single folder, and shuffled into a random order prior to scoring, with the observer unaware of the photograph location or species during the scoring process. Birds were also assigned a binary score of 0 or 1 based on whether the species or morph in question had uniformly-coloured facial plumage without definable malar stripes, to enable the analysis to be rerun on a subset of the dataset with these birds excluded.
Ecological and biometric data for the 39 falcon species (body mass (g), hand-wing index), prey preference, and habitat openness) were then sourced from AVONET (https://opentraits.org/datasets/avonet.html) and supplementary sources in the literature. Species were assigned a "prey preference" score of 1-4 based on the proportion of bird prey in the diet, with a higher score representing a higher degree of specialisation on bird prey, and a "habitat openness" score of 1-5 based on the degree of dependence on forest habitats, with higher scores representing more open (less forested) habitats. Species trait data were collected between January and April 2022.